File: C:/Users/fred/anaconda3/Lib/site-packages/datashader/colors.py
from __future__ import annotations
# Lookup of web color names to their hex codes.
color_lookup = {'aliceblue': '#F0F8FF', 'antiquewhite': '#FAEBD7',
'aqua': '#00FFFF', 'aquamarine': '#7FFFD4',
'azure': '#F0FFFF', 'beige': '#F5F5DC',
'bisque': '#FFE4C4', 'black': '#000000',
'blanchedalmond': '#FFEBCD', 'blue': '#0000FF',
'blueviolet': '#8A2BE2', 'brown': '#A52A2A',
'burlywood': '#DEB887', 'cadetblue': '#5F9EA0',
'chartreuse': '#7FFF00', 'chocolate': '#D2691E',
'coral': '#FF7F50', 'cornflowerblue': '#6495ED',
'cornsilk': '#FFF8DC', 'crimson': '#DC143C',
'cyan': '#00FFFF', 'darkblue': '#00008B',
'darkcyan': '#008B8B', 'darkgoldenrod': '#B8860B',
'darkgray': '#A9A9A9', 'darkgreen': '#006400',
'darkgrey': '#A9A9A9', 'darkkhaki': '#BDB76B',
'darkmagenta': '#8B008B', 'darkolivegreen': '#556B2F',
'darkorange': '#FF8C00', 'darkorchid': '#9932CC',
'darkred': '#8B0000', 'darksage': '#598556',
'darksalmon': '#E9967A', 'darkseagreen': '#8FBC8F',
'darkslateblue': '#483D8B', 'darkslategray': '#2F4F4F',
'darkslategrey': '#2F4F4F', 'darkturquoise': '#00CED1',
'darkviolet': '#9400D3', 'deeppink': '#FF1493',
'deepskyblue': '#00BFFF', 'dimgray': '#696969',
'dimgrey': '#696969', 'dodgerblue': '#1E90FF',
'firebrick': '#B22222', 'floralwhite': '#FFFAF0',
'forestgreen': '#228B22', 'fuchsia': '#FF00FF',
'gainsboro': '#DCDCDC', 'ghostwhite': '#F8F8FF',
'gold': '#FFD700', 'goldenrod': '#DAA520',
'gray': '#808080', 'green': '#008000',
'greenyellow': '#ADFF2F', 'grey': '#808080',
'honeydew': '#F0FFF0', 'hotpink': '#FF69B4',
'indianred': '#CD5C5C', 'indigo': '#4B0082',
'ivory': '#FFFFF0', 'khaki': '#F0E68C',
'lavender': '#E6E6FA', 'lavenderblush': '#FFF0F5',
'lawngreen': '#7CFC00', 'lemonchiffon': '#FFFACD',
'lightblue': '#ADD8E6', 'lightcoral': '#F08080',
'lightcyan': '#E0FFFF', 'lightgoldenrodyellow': '#FAFAD2',
'lightgray': '#D3D3D3', 'lightgreen': '#90EE90',
'lightgrey': '#D3D3D3', 'lightpink': '#FFB6C1',
'lightsage': '#BCECAC', 'lightsalmon': '#FFA07A',
'lightseagreen': '#20B2AA', 'lightskyblue': '#87CEFA',
'lightslategray': '#778899', 'lightslategrey': '#778899',
'lightsteelblue': '#B0C4DE', 'lightyellow': '#FFFFE0',
'lime': '#00FF00', 'limegreen': '#32CD32',
'linen': '#FAF0E6', 'magenta': '#FF00FF',
'maroon': '#800000', 'mediumaquamarine': '#66CDAA',
'mediumblue': '#0000CD', 'mediumorchid': '#BA55D3',
'mediumpurple': '#9370DB', 'mediumseagreen': '#3CB371',
'mediumslateblue': '#7B68EE', 'mediumspringgreen': '#00FA9A',
'mediumturquoise': '#48D1CC', 'mediumvioletred': '#C71585',
'midnightblue': '#191970', 'mintcream': '#F5FFFA',
'mistyrose': '#FFE4E1', 'moccasin': '#FFE4B5',
'navajowhite': '#FFDEAD', 'navy': '#000080',
'oldlace': '#FDF5E6', 'olive': '#808000',
'olivedrab': '#6B8E23', 'orange': '#FFA500',
'orangered': '#FF4500', 'orchid': '#DA70D6',
'palegoldenrod': '#EEE8AA', 'palegreen': '#98FB98',
'paleturquoise': '#AFEEEE', 'palevioletred': '#DB7093',
'papayawhip': '#FFEFD5', 'peachpuff': '#FFDAB9',
'peru': '#CD853F', 'pink': '#FFC0CB',
'plum': '#DDA0DD', 'powderblue': '#B0E0E6',
'purple': '#800080', 'red': '#FF0000',
'rosybrown': '#BC8F8F', 'royalblue': '#4169E1',
'saddlebrown': '#8B4513', 'sage': '#87AE73',
'salmon': '#FA8072', 'sandybrown': '#FAA460',
'seagreen': '#2E8B57', 'seashell': '#FFF5EE',
'sienna': '#A0522D', 'silver': '#C0C0C0',
'skyblue': '#87CEEB', 'slateblue': '#6A5ACD',
'slategray': '#708090', 'slategrey': '#708090',
'snow': '#FFFAFA', 'springgreen': '#00FF7F',
'steelblue': '#4682B4', 'tan': '#D2B48C',
'teal': '#008080', 'thistle': '#D8BFD8',
'tomato': '#FF6347', 'turquoise': '#40E0D0',
'violet': '#EE82EE', 'wheat': '#F5DEB3',
'white': '#FFFFFF', 'whitesmoke': '#F5F5F5',
'yellow': '#FFFF00', 'yellowgreen': '#9ACD32'}
def hex_to_rgb(x):
"""Convert a color hexcode to an rgb tuple.
Example
-------
>>> rgb('#FFFFFF')
(255, 255, 255)
"""
if not (x.startswith('#') and len(x) == 7):
raise ValueError("Invalid hex color")
x = x.strip('#')
try:
return (int(x[:2], 16), int(x[2:4], 16), int(x[4:], 16))
except ValueError:
raise ValueError("Invalid hex color")
def rgb(x):
"""Return a triple representing rgb color.
Can convert colors by name or hexcode. Passing in a valid rgb tuple is
idempotent.
Example
-------
>>> rgb('plum')
(221, 160, 221)
>>> rgb('#FFFFFF')
(255, 255, 255)
>>> rgb((255, 255, 255))
(255, 255, 255)
"""
if isinstance(x, str):
if x.startswith('#'):
return hex_to_rgb(x)
elif x in color_lookup:
return hex_to_rgb(color_lookup[x])
else:
raise ValueError("Unknown color: '{0}'".format(x))
elif isinstance(x, tuple) and len(x) == 3:
if min(x) < 0 or max(x) > 255:
raise ValueError("Invalid RGB tuple")
else:
raise TypeError("Don't know how to convert {0} to RGB".format(x))
return x
# Example palettes
# Copied from from bokeh.palettes.Greys9
Greys9 = ["#000000", "#252525", "#525252", "#737373", "#969696", "#bdbdbd", "#d9d9d9", "#f0f0f0", "#ffffff"] # noqa: E501
# Adapted from matplotlib.cm.hot to be more uniform at the high end
Hot = ["black", "maroon", "darkred", "red", "orangered", "darkorange", "orange", "gold", "yellow", "white"] # noqa: E501
# pseudo terrestrial elevation ramp
Elevation = ["aqua", "sandybrown", "limegreen", "green", "green", "darkgreen", "saddlebrown", "gray", "white"] # noqa: E501
# Qualitative color maps, for use in colorizing categories
# Originally from Cynthia Brewer (http://colorbrewer2.org), via Bokeh
Set1 = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf', '#999999'] # noqa: E501
Set2 = ['#66c2a5', '#fc8d62', '#8da0cb', '#e78ac3', '#a6d854', '#ffd92f', '#e5c494', '#b3b3b3']
Set3 = ['#8dd3c7', '#ffffb3', '#bebada', '#fb8072', '#80b1d3', '#fdb462', '#b3de69', '#fccde5', '#d9d9d9', '#bc80bd', '#ccebc5', '#ffed6f'] # noqa: E501
# Sets 1, 2, and 3 combined, minus indistinguishable colors
Sets1to3 = Set1+Set2[0:3]+Set2[4:7]+Set3[1:2]+Set3[3:4]+Set3[5:6]+Set3[7:9]+Set3[10:]
def _mpl_cmdata_to_bokeh_palette(cm_data):
"""Given the data from a Matplotlib colormap as a list of three-item lists in the range 0,1.0,
convert colors into the range 0,256 and return as a list of tuples"""
return [(int(r*256),int(g*256),int(b*256)) for r,g,b in cm_data]
# Copied from matplotlib/_cm_listed.py
_inferno_data = [[0.001462, 0.000466, 0.013866],
[0.002267, 0.001270, 0.018570],
[0.003299, 0.002249, 0.024239],
[0.004547, 0.003392, 0.030909],
[0.006006, 0.004692, 0.038558],
[0.007676, 0.006136, 0.046836],
[0.009561, 0.007713, 0.055143],
[0.011663, 0.009417, 0.063460],
[0.013995, 0.011225, 0.071862],
[0.016561, 0.013136, 0.080282],
[0.019373, 0.015133, 0.088767],
[0.022447, 0.017199, 0.097327],
[0.025793, 0.019331, 0.105930],
[0.029432, 0.021503, 0.114621],
[0.033385, 0.023702, 0.123397],
[0.037668, 0.025921, 0.132232],
[0.042253, 0.028139, 0.141141],
[0.046915, 0.030324, 0.150164],
[0.051644, 0.032474, 0.159254],
[0.056449, 0.034569, 0.168414],
[0.061340, 0.036590, 0.177642],
[0.066331, 0.038504, 0.186962],
[0.071429, 0.040294, 0.196354],
[0.076637, 0.041905, 0.205799],
[0.081962, 0.043328, 0.215289],
[0.087411, 0.044556, 0.224813],
[0.092990, 0.045583, 0.234358],
[0.098702, 0.046402, 0.243904],
[0.104551, 0.047008, 0.253430],
[0.110536, 0.047399, 0.262912],
[0.116656, 0.047574, 0.272321],
[0.122908, 0.047536, 0.281624],
[0.129285, 0.047293, 0.290788],
[0.135778, 0.046856, 0.299776],
[0.142378, 0.046242, 0.308553],
[0.149073, 0.045468, 0.317085],
[0.155850, 0.044559, 0.325338],
[0.162689, 0.043554, 0.333277],
[0.169575, 0.042489, 0.340874],
[0.176493, 0.041402, 0.348111],
[0.183429, 0.040329, 0.354971],
[0.190367, 0.039309, 0.361447],
[0.197297, 0.038400, 0.367535],
[0.204209, 0.037632, 0.373238],
[0.211095, 0.037030, 0.378563],
[0.217949, 0.036615, 0.383522],
[0.224763, 0.036405, 0.388129],
[0.231538, 0.036405, 0.392400],
[0.238273, 0.036621, 0.396353],
[0.244967, 0.037055, 0.400007],
[0.251620, 0.037705, 0.403378],
[0.258234, 0.038571, 0.406485],
[0.264810, 0.039647, 0.409345],
[0.271347, 0.040922, 0.411976],
[0.277850, 0.042353, 0.414392],
[0.284321, 0.043933, 0.416608],
[0.290763, 0.045644, 0.418637],
[0.297178, 0.047470, 0.420491],
[0.303568, 0.049396, 0.422182],
[0.309935, 0.051407, 0.423721],
[0.316282, 0.053490, 0.425116],
[0.322610, 0.055634, 0.426377],
[0.328921, 0.057827, 0.427511],
[0.335217, 0.060060, 0.428524],
[0.341500, 0.062325, 0.429425],
[0.347771, 0.064616, 0.430217],
[0.354032, 0.066925, 0.430906],
[0.360284, 0.069247, 0.431497],
[0.366529, 0.071579, 0.431994],
[0.372768, 0.073915, 0.432400],
[0.379001, 0.076253, 0.432719],
[0.385228, 0.078591, 0.432955],
[0.391453, 0.080927, 0.433109],
[0.397674, 0.083257, 0.433183],
[0.403894, 0.085580, 0.433179],
[0.410113, 0.087896, 0.433098],
[0.416331, 0.090203, 0.432943],
[0.422549, 0.092501, 0.432714],
[0.428768, 0.094790, 0.432412],
[0.434987, 0.097069, 0.432039],
[0.441207, 0.099338, 0.431594],
[0.447428, 0.101597, 0.431080],
[0.453651, 0.103848, 0.430498],
[0.459875, 0.106089, 0.429846],
[0.466100, 0.108322, 0.429125],
[0.472328, 0.110547, 0.428334],
[0.478558, 0.112764, 0.427475],
[0.484789, 0.114974, 0.426548],
[0.491022, 0.117179, 0.425552],
[0.497257, 0.119379, 0.424488],
[0.503493, 0.121575, 0.423356],
[0.509730, 0.123769, 0.422156],
[0.515967, 0.125960, 0.420887],
[0.522206, 0.128150, 0.419549],
[0.528444, 0.130341, 0.418142],
[0.534683, 0.132534, 0.416667],
[0.540920, 0.134729, 0.415123],
[0.547157, 0.136929, 0.413511],
[0.553392, 0.139134, 0.411829],
[0.559624, 0.141346, 0.410078],
[0.565854, 0.143567, 0.408258],
[0.572081, 0.145797, 0.406369],
[0.578304, 0.148039, 0.404411],
[0.584521, 0.150294, 0.402385],
[0.590734, 0.152563, 0.400290],
[0.596940, 0.154848, 0.398125],
[0.603139, 0.157151, 0.395891],
[0.609330, 0.159474, 0.393589],
[0.615513, 0.161817, 0.391219],
[0.621685, 0.164184, 0.388781],
[0.627847, 0.166575, 0.386276],
[0.633998, 0.168992, 0.383704],
[0.640135, 0.171438, 0.381065],
[0.646260, 0.173914, 0.378359],
[0.652369, 0.176421, 0.375586],
[0.658463, 0.178962, 0.372748],
[0.664540, 0.181539, 0.369846],
[0.670599, 0.184153, 0.366879],
[0.676638, 0.186807, 0.363849],
[0.682656, 0.189501, 0.360757],
[0.688653, 0.192239, 0.357603],
[0.694627, 0.195021, 0.354388],
[0.700576, 0.197851, 0.351113],
[0.706500, 0.200728, 0.347777],
[0.712396, 0.203656, 0.344383],
[0.718264, 0.206636, 0.340931],
[0.724103, 0.209670, 0.337424],
[0.729909, 0.212759, 0.333861],
[0.735683, 0.215906, 0.330245],
[0.741423, 0.219112, 0.326576],
[0.747127, 0.222378, 0.322856],
[0.752794, 0.225706, 0.319085],
[0.758422, 0.229097, 0.315266],
[0.764010, 0.232554, 0.311399],
[0.769556, 0.236077, 0.307485],
[0.775059, 0.239667, 0.303526],
[0.780517, 0.243327, 0.299523],
[0.785929, 0.247056, 0.295477],
[0.791293, 0.250856, 0.291390],
[0.796607, 0.254728, 0.287264],
[0.801871, 0.258674, 0.283099],
[0.807082, 0.262692, 0.278898],
[0.812239, 0.266786, 0.274661],
[0.817341, 0.270954, 0.270390],
[0.822386, 0.275197, 0.266085],
[0.827372, 0.279517, 0.261750],
[0.832299, 0.283913, 0.257383],
[0.837165, 0.288385, 0.252988],
[0.841969, 0.292933, 0.248564],
[0.846709, 0.297559, 0.244113],
[0.851384, 0.302260, 0.239636],
[0.855992, 0.307038, 0.235133],
[0.860533, 0.311892, 0.230606],
[0.865006, 0.316822, 0.226055],
[0.869409, 0.321827, 0.221482],
[0.873741, 0.326906, 0.216886],
[0.878001, 0.332060, 0.212268],
[0.882188, 0.337287, 0.207628],
[0.886302, 0.342586, 0.202968],
[0.890341, 0.347957, 0.198286],
[0.894305, 0.353399, 0.193584],
[0.898192, 0.358911, 0.188860],
[0.902003, 0.364492, 0.184116],
[0.905735, 0.370140, 0.179350],
[0.909390, 0.375856, 0.174563],
[0.912966, 0.381636, 0.169755],
[0.916462, 0.387481, 0.164924],
[0.919879, 0.393389, 0.160070],
[0.923215, 0.399359, 0.155193],
[0.926470, 0.405389, 0.150292],
[0.929644, 0.411479, 0.145367],
[0.932737, 0.417627, 0.140417],
[0.935747, 0.423831, 0.135440],
[0.938675, 0.430091, 0.130438],
[0.941521, 0.436405, 0.125409],
[0.944285, 0.442772, 0.120354],
[0.946965, 0.449191, 0.115272],
[0.949562, 0.455660, 0.110164],
[0.952075, 0.462178, 0.105031],
[0.954506, 0.468744, 0.099874],
[0.956852, 0.475356, 0.094695],
[0.959114, 0.482014, 0.089499],
[0.961293, 0.488716, 0.084289],
[0.963387, 0.495462, 0.079073],
[0.965397, 0.502249, 0.073859],
[0.967322, 0.509078, 0.068659],
[0.969163, 0.515946, 0.063488],
[0.970919, 0.522853, 0.058367],
[0.972590, 0.529798, 0.053324],
[0.974176, 0.536780, 0.048392],
[0.975677, 0.543798, 0.043618],
[0.977092, 0.550850, 0.039050],
[0.978422, 0.557937, 0.034931],
[0.979666, 0.565057, 0.031409],
[0.980824, 0.572209, 0.028508],
[0.981895, 0.579392, 0.026250],
[0.982881, 0.586606, 0.024661],
[0.983779, 0.593849, 0.023770],
[0.984591, 0.601122, 0.023606],
[0.985315, 0.608422, 0.024202],
[0.985952, 0.615750, 0.025592],
[0.986502, 0.623105, 0.027814],
[0.986964, 0.630485, 0.030908],
[0.987337, 0.637890, 0.034916],
[0.987622, 0.645320, 0.039886],
[0.987819, 0.652773, 0.045581],
[0.987926, 0.660250, 0.051750],
[0.987945, 0.667748, 0.058329],
[0.987874, 0.675267, 0.065257],
[0.987714, 0.682807, 0.072489],
[0.987464, 0.690366, 0.079990],
[0.987124, 0.697944, 0.087731],
[0.986694, 0.705540, 0.095694],
[0.986175, 0.713153, 0.103863],
[0.985566, 0.720782, 0.112229],
[0.984865, 0.728427, 0.120785],
[0.984075, 0.736087, 0.129527],
[0.983196, 0.743758, 0.138453],
[0.982228, 0.751442, 0.147565],
[0.981173, 0.759135, 0.156863],
[0.980032, 0.766837, 0.166353],
[0.978806, 0.774545, 0.176037],
[0.977497, 0.782258, 0.185923],
[0.976108, 0.789974, 0.196018],
[0.974638, 0.797692, 0.206332],
[0.973088, 0.805409, 0.216877],
[0.971468, 0.813122, 0.227658],
[0.969783, 0.820825, 0.238686],
[0.968041, 0.828515, 0.249972],
[0.966243, 0.836191, 0.261534],
[0.964394, 0.843848, 0.273391],
[0.962517, 0.851476, 0.285546],
[0.960626, 0.859069, 0.298010],
[0.958720, 0.866624, 0.310820],
[0.956834, 0.874129, 0.323974],
[0.954997, 0.881569, 0.337475],
[0.953215, 0.888942, 0.351369],
[0.951546, 0.896226, 0.365627],
[0.950018, 0.903409, 0.380271],
[0.948683, 0.910473, 0.395289],
[0.947594, 0.917399, 0.410665],
[0.946809, 0.924168, 0.426373],
[0.946392, 0.930761, 0.442367],
[0.946403, 0.937159, 0.458592],
[0.946903, 0.943348, 0.474970],
[0.947937, 0.949318, 0.491426],
[0.949545, 0.955063, 0.507860],
[0.951740, 0.960587, 0.524203],
[0.954529, 0.965896, 0.540361],
[0.957896, 0.971003, 0.556275],
[0.961812, 0.975924, 0.571925],
[0.966249, 0.980678, 0.587206],
[0.971162, 0.985282, 0.602154],
[0.976511, 0.989753, 0.616760],
[0.982257, 0.994109, 0.631017],
[0.988362, 0.998364, 0.644924]]
inferno = _mpl_cmdata_to_bokeh_palette(_inferno_data)
# Copied from matplotlib/_cm_listed.py
_viridis_data = [[0.267004, 0.004874, 0.329415],
[0.268510, 0.009605, 0.335427],
[0.269944, 0.014625, 0.341379],
[0.271305, 0.019942, 0.347269],
[0.272594, 0.025563, 0.353093],
[0.273809, 0.031497, 0.358853],
[0.274952, 0.037752, 0.364543],
[0.276022, 0.044167, 0.370164],
[0.277018, 0.050344, 0.375715],
[0.277941, 0.056324, 0.381191],
[0.278791, 0.062145, 0.386592],
[0.279566, 0.067836, 0.391917],
[0.280267, 0.073417, 0.397163],
[0.280894, 0.078907, 0.402329],
[0.281446, 0.084320, 0.407414],
[0.281924, 0.089666, 0.412415],
[0.282327, 0.094955, 0.417331],
[0.282656, 0.100196, 0.422160],
[0.282910, 0.105393, 0.426902],
[0.283091, 0.110553, 0.431554],
[0.283197, 0.115680, 0.436115],
[0.283229, 0.120777, 0.440584],
[0.283187, 0.125848, 0.444960],
[0.283072, 0.130895, 0.449241],
[0.282884, 0.135920, 0.453427],
[0.282623, 0.140926, 0.457517],
[0.282290, 0.145912, 0.461510],
[0.281887, 0.150881, 0.465405],
[0.281412, 0.155834, 0.469201],
[0.280868, 0.160771, 0.472899],
[0.280255, 0.165693, 0.476498],
[0.279574, 0.170599, 0.479997],
[0.278826, 0.175490, 0.483397],
[0.278012, 0.180367, 0.486697],
[0.277134, 0.185228, 0.489898],
[0.276194, 0.190074, 0.493001],
[0.275191, 0.194905, 0.496005],
[0.274128, 0.199721, 0.498911],
[0.273006, 0.204520, 0.501721],
[0.271828, 0.209303, 0.504434],
[0.270595, 0.214069, 0.507052],
[0.269308, 0.218818, 0.509577],
[0.267968, 0.223549, 0.512008],
[0.266580, 0.228262, 0.514349],
[0.265145, 0.232956, 0.516599],
[0.263663, 0.237631, 0.518762],
[0.262138, 0.242286, 0.520837],
[0.260571, 0.246922, 0.522828],
[0.258965, 0.251537, 0.524736],
[0.257322, 0.256130, 0.526563],
[0.255645, 0.260703, 0.528312],
[0.253935, 0.265254, 0.529983],
[0.252194, 0.269783, 0.531579],
[0.250425, 0.274290, 0.533103],
[0.248629, 0.278775, 0.534556],
[0.246811, 0.283237, 0.535941],
[0.244972, 0.287675, 0.537260],
[0.243113, 0.292092, 0.538516],
[0.241237, 0.296485, 0.539709],
[0.239346, 0.300855, 0.540844],
[0.237441, 0.305202, 0.541921],
[0.235526, 0.309527, 0.542944],
[0.233603, 0.313828, 0.543914],
[0.231674, 0.318106, 0.544834],
[0.229739, 0.322361, 0.545706],
[0.227802, 0.326594, 0.546532],
[0.225863, 0.330805, 0.547314],
[0.223925, 0.334994, 0.548053],
[0.221989, 0.339161, 0.548752],
[0.220057, 0.343307, 0.549413],
[0.218130, 0.347432, 0.550038],
[0.216210, 0.351535, 0.550627],
[0.214298, 0.355619, 0.551184],
[0.212395, 0.359683, 0.551710],
[0.210503, 0.363727, 0.552206],
[0.208623, 0.367752, 0.552675],
[0.206756, 0.371758, 0.553117],
[0.204903, 0.375746, 0.553533],
[0.203063, 0.379716, 0.553925],
[0.201239, 0.383670, 0.554294],
[0.199430, 0.387607, 0.554642],
[0.197636, 0.391528, 0.554969],
[0.195860, 0.395433, 0.555276],
[0.194100, 0.399323, 0.555565],
[0.192357, 0.403199, 0.555836],
[0.190631, 0.407061, 0.556089],
[0.188923, 0.410910, 0.556326],
[0.187231, 0.414746, 0.556547],
[0.185556, 0.418570, 0.556753],
[0.183898, 0.422383, 0.556944],
[0.182256, 0.426184, 0.557120],
[0.180629, 0.429975, 0.557282],
[0.179019, 0.433756, 0.557430],
[0.177423, 0.437527, 0.557565],
[0.175841, 0.441290, 0.557685],
[0.174274, 0.445044, 0.557792],
[0.172719, 0.448791, 0.557885],
[0.171176, 0.452530, 0.557965],
[0.169646, 0.456262, 0.558030],
[0.168126, 0.459988, 0.558082],
[0.166617, 0.463708, 0.558119],
[0.165117, 0.467423, 0.558141],
[0.163625, 0.471133, 0.558148],
[0.162142, 0.474838, 0.558140],
[0.160665, 0.478540, 0.558115],
[0.159194, 0.482237, 0.558073],
[0.157729, 0.485932, 0.558013],
[0.156270, 0.489624, 0.557936],
[0.154815, 0.493313, 0.557840],
[0.153364, 0.497000, 0.557724],
[0.151918, 0.500685, 0.557587],
[0.150476, 0.504369, 0.557430],
[0.149039, 0.508051, 0.557250],
[0.147607, 0.511733, 0.557049],
[0.146180, 0.515413, 0.556823],
[0.144759, 0.519093, 0.556572],
[0.143343, 0.522773, 0.556295],
[0.141935, 0.526453, 0.555991],
[0.140536, 0.530132, 0.555659],
[0.139147, 0.533812, 0.555298],
[0.137770, 0.537492, 0.554906],
[0.136408, 0.541173, 0.554483],
[0.135066, 0.544853, 0.554029],
[0.133743, 0.548535, 0.553541],
[0.132444, 0.552216, 0.553018],
[0.131172, 0.555899, 0.552459],
[0.129933, 0.559582, 0.551864],
[0.128729, 0.563265, 0.551229],
[0.127568, 0.566949, 0.550556],
[0.126453, 0.570633, 0.549841],
[0.125394, 0.574318, 0.549086],
[0.124395, 0.578002, 0.548287],
[0.123463, 0.581687, 0.547445],
[0.122606, 0.585371, 0.546557],
[0.121831, 0.589055, 0.545623],
[0.121148, 0.592739, 0.544641],
[0.120565, 0.596422, 0.543611],
[0.120092, 0.600104, 0.542530],
[0.119738, 0.603785, 0.541400],
[0.119512, 0.607464, 0.540218],
[0.119423, 0.611141, 0.538982],
[0.119483, 0.614817, 0.537692],
[0.119699, 0.618490, 0.536347],
[0.120081, 0.622161, 0.534946],
[0.120638, 0.625828, 0.533488],
[0.121380, 0.629492, 0.531973],
[0.122312, 0.633153, 0.530398],
[0.123444, 0.636809, 0.528763],
[0.124780, 0.640461, 0.527068],
[0.126326, 0.644107, 0.525311],
[0.128087, 0.647749, 0.523491],
[0.130067, 0.651384, 0.521608],
[0.132268, 0.655014, 0.519661],
[0.134692, 0.658636, 0.517649],
[0.137339, 0.662252, 0.515571],
[0.140210, 0.665859, 0.513427],
[0.143303, 0.669459, 0.511215],
[0.146616, 0.673050, 0.508936],
[0.150148, 0.676631, 0.506589],
[0.153894, 0.680203, 0.504172],
[0.157851, 0.683765, 0.501686],
[0.162016, 0.687316, 0.499129],
[0.166383, 0.690856, 0.496502],
[0.170948, 0.694384, 0.493803],
[0.175707, 0.697900, 0.491033],
[0.180653, 0.701402, 0.488189],
[0.185783, 0.704891, 0.485273],
[0.191090, 0.708366, 0.482284],
[0.196571, 0.711827, 0.479221],
[0.202219, 0.715272, 0.476084],
[0.208030, 0.718701, 0.472873],
[0.214000, 0.722114, 0.469588],
[0.220124, 0.725509, 0.466226],
[0.226397, 0.728888, 0.462789],
[0.232815, 0.732247, 0.459277],
[0.239374, 0.735588, 0.455688],
[0.246070, 0.738910, 0.452024],
[0.252899, 0.742211, 0.448284],
[0.259857, 0.745492, 0.444467],
[0.266941, 0.748751, 0.440573],
[0.274149, 0.751988, 0.436601],
[0.281477, 0.755203, 0.432552],
[0.288921, 0.758394, 0.428426],
[0.296479, 0.761561, 0.424223],
[0.304148, 0.764704, 0.419943],
[0.311925, 0.767822, 0.415586],
[0.319809, 0.770914, 0.411152],
[0.327796, 0.773980, 0.406640],
[0.335885, 0.777018, 0.402049],
[0.344074, 0.780029, 0.397381],
[0.352360, 0.783011, 0.392636],
[0.360741, 0.785964, 0.387814],
[0.369214, 0.788888, 0.382914],
[0.377779, 0.791781, 0.377939],
[0.386433, 0.794644, 0.372886],
[0.395174, 0.797475, 0.367757],
[0.404001, 0.800275, 0.362552],
[0.412913, 0.803041, 0.357269],
[0.421908, 0.805774, 0.351910],
[0.430983, 0.808473, 0.346476],
[0.440137, 0.811138, 0.340967],
[0.449368, 0.813768, 0.335384],
[0.458674, 0.816363, 0.329727],
[0.468053, 0.818921, 0.323998],
[0.477504, 0.821444, 0.318195],
[0.487026, 0.823929, 0.312321],
[0.496615, 0.826376, 0.306377],
[0.506271, 0.828786, 0.300362],
[0.515992, 0.831158, 0.294279],
[0.525776, 0.833491, 0.288127],
[0.535621, 0.835785, 0.281908],
[0.545524, 0.838039, 0.275626],
[0.555484, 0.840254, 0.269281],
[0.565498, 0.842430, 0.262877],
[0.575563, 0.844566, 0.256415],
[0.585678, 0.846661, 0.249897],
[0.595839, 0.848717, 0.243329],
[0.606045, 0.850733, 0.236712],
[0.616293, 0.852709, 0.230052],
[0.626579, 0.854645, 0.223353],
[0.636902, 0.856542, 0.216620],
[0.647257, 0.858400, 0.209861],
[0.657642, 0.860219, 0.203082],
[0.668054, 0.861999, 0.196293],
[0.678489, 0.863742, 0.189503],
[0.688944, 0.865448, 0.182725],
[0.699415, 0.867117, 0.175971],
[0.709898, 0.868751, 0.169257],
[0.720391, 0.870350, 0.162603],
[0.730889, 0.871916, 0.156029],
[0.741388, 0.873449, 0.149561],
[0.751884, 0.874951, 0.143228],
[0.762373, 0.876424, 0.137064],
[0.772852, 0.877868, 0.131109],
[0.783315, 0.879285, 0.125405],
[0.793760, 0.880678, 0.120005],
[0.804182, 0.882046, 0.114965],
[0.814576, 0.883393, 0.110347],
[0.824940, 0.884720, 0.106217],
[0.835270, 0.886029, 0.102646],
[0.845561, 0.887322, 0.099702],
[0.855810, 0.888601, 0.097452],
[0.866013, 0.889868, 0.095953],
[0.876168, 0.891125, 0.095250],
[0.886271, 0.892374, 0.095374],
[0.896320, 0.893616, 0.096335],
[0.906311, 0.894855, 0.098125],
[0.916242, 0.896091, 0.100717],
[0.926106, 0.897330, 0.104071],
[0.935904, 0.898570, 0.108131],
[0.945636, 0.899815, 0.112838],
[0.955300, 0.901065, 0.118128],
[0.964894, 0.902323, 0.123941],
[0.974417, 0.903590, 0.130215],
[0.983868, 0.904867, 0.136897],
[0.993248, 0.906157, 0.143936]]
viridis = _mpl_cmdata_to_bokeh_palette(_viridis_data)
def colormap_select(base_colormap, start=0, end=1.0, reverse=False):
"""
Given a colormap in the form of a list, such as a Bokeh palette,
return a version of the colormap reversed if requested, and selecting
a subset (on a scale 0,1.0) of the elements in the colormap list.
For instance:
>>> cmap = ["#000000", "#969696", "#d9d9d9", "#ffffff"]
>>> colormap_select(cmap,reverse=True)
['#ffffff', '#d9d9d9', '#969696', '#000000']
>>> colormap_select(cmap,0.3,reverse=True)
['#d9d9d9', '#969696', '#000000']
"""
full = list(reversed(base_colormap) if reverse else base_colormap)
num = len(full)
return full[int(start*num):int(end*num)]